Advances in Deep Learning: Architectures, Applications, and Future Directions
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Abstract
Deep learning has revolutionized artificial intelligence by enabling unprecedented advancements in tasks such as image recognition, natural language processing, and autonomous systems. This paper explores the latest developments in deep learning architectures, highlights key applications, and identifies emerging trends and challenges. A novel framework for enhancing model efficiency and scalability through innovative training techniques is proposed.
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